A Method and System for CO2 Time-Shift Analysis Based on Zero-Bias DAS-VSP Data

Abstract

This invention relates to the field of petroleum exploration and development technology, and discloses a method comprising: collecting zero-biased DAS-VSP data at different times, wherein the zero-biased DAS-VSP data includes basic data and monitoring data at different times; selecting data from the basic data and the monitoring data at depths with a signal-to-noise ratio higher than a first threshold as first intermediate data and second intermediate data, respectively; separating the first intermediate data and the second intermediate data to obtain corresponding up-reflection wavefield data; using the up-reflection wavefield data from the basic data and the monitoring data to pick the first arrival time of the up-reflection wavefield and the second arrival time of the up-reflection wavefield at different locations, respectively; performing cross-correlation time difference calculation on the first arrival time of the up-reflection wavefield at different locations and the second arrival time of the up-reflection wavefield at different times, and finally performing time-shift analysis of CO2. This invention can analyze and monitor the distribution and dynamic changes of underground carbon dioxide.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration and development technology, specifically to a CO2 time-shift analysis method and system based on zero-biased DAS-VSP data. Background Technology

[0002] In recent years, time-lapse seismic monitoring technology has developed rapidly. National requirements for low-carbon and green development have accelerated CO2 emissions, driving the development of CCS (Carbon Capture and Storage) technology. CCS involves capturing carbon dioxide released into the atmosphere, compressing it, and storing it in depleted oil fields or other safe underground locations. Developing a long-term, stable carbon dioxide geological storage monitoring system is a crucial application area for geophysics to expand into new markets. Leveraging deep learning and comprehensively utilizing multiple geophysical methods to monitor carbon dioxide geological storage projects is a future development trend.

[0003] Therefore, designing a fast and simple method for CO2 time-shift analysis is an urgent matter. Summary of the Invention

[0004] This invention provides a method and system for CO2 time-shift analysis based on zero-biased DAS-VSP data, so as to achieve rapid and simple CO2 time-shift analysis.

[0005] This invention is achieved through the following technical solution:

[0006] A method for CO2 time-shift analysis based on zero-biased DAS-VSP data includes:

[0007] Zero-bias DAS-VSP data were collected at different times. The zero-bias DAS-VSP data included basic data and monitoring data at different times. The basic data included VSP data detected when no CO2 was injected, and the monitoring data included VSP data after CO2 was injected.

[0008] Data with a signal-to-noise ratio higher than a first threshold are selected from the basic data and the monitoring data, respectively, as the first intermediate data and the second intermediate data.

[0009] The first intermediate data and the second intermediate data are separated to obtain the corresponding first uplink reflected wave field data and second uplink reflected wave field data;

[0010] The first arrival time of the uplink reflected wave field at different positions is picked from the first uplink reflected wave field data and the second uplink reflected wave field data respectively. Let the first arrival time of the uplink reflected wave field corresponding to the first uplink reflected wave field data be the first uplink reflected wave field first arrival time, and let the first arrival time of the uplink reflected wave field corresponding to the second uplink reflected wave field data be the second uplink reflected wave field first arrival time.

[0011] The first arrival times of the first up-reflected wave field at different locations and the first arrival times of the second up-reflected wave field at different times are cross-correlated to obtain the time difference, and finally the pre-stack time difference analysis results at different times are obtained. CO2 time shift analysis is performed based on the pre-stack time difference analysis results at different times.

[0012] As an optimization, when performing the direct wave first arrival pickup operation from the basic data and the monitoring data, a depth segment with a data signal-to-noise ratio higher than a set first threshold is selected for direct wave first arrival pickup.

[0013] As an optimization, the specific process of separating the first intermediate data to obtain the first uplink reflected wavefield data is as follows:

[0014] The first intermediate data is deconvolved to eliminate the influence of multiple waves on the up-wave field analysis, resulting in the third intermediate data.

[0015] Wavefield separation is performed on the third intermediate data to remove the downlink wavefield data, thereby obtaining the first uplink reflected wavefield data.

[0016] As an optimization, the specific process for separating the second uplink reflected wavefield data from the second intermediate data is as follows:

[0017] The second intermediate data is deconvolved to eliminate the influence of multiple waves on the up-wave field analysis, resulting in the fourth intermediate data.

[0018] Wavefield separation is performed on the fourth intermediate data to remove the downlink wavefield data, thereby obtaining the second uplink reflected wavefield data.

[0019] As an optimization, the arrival times of the up-reflected wave field at different locations are picked up, including the upper, lower, and lower gas injection layers.

[0020] As an optimization, the first threshold is 20 dB.

[0021] As an optimization, after removing the downlink wave field data, waveforms in depth segments with a signal-to-noise ratio higher than the second threshold are selected as uplink reflected wave field data.

[0022] As an optimization, the second threshold is 30 dB.

[0023] As an optimization, the gas injection layer, the upper gas injection layer, and the lower gas injection layer are all located in depth segments where the data signal-to-noise ratio is higher than a set first threshold.

[0024] As an optimization, the first arrival times of the first uplink reflected wavefield at different locations and the first arrival times of the second uplink reflected wavefield at different times are cross-correlated to calculate the time difference. The specific engineering process for obtaining the pre-stack time difference analysis results at different times is as follows:

[0025] A1. For the first arrival time of the second uplink reflected wave field at different locations corresponding to the monitoring data of a certain period, the first arrival time of the first uplink reflected wave field and the first arrival time of the second uplink reflected wave field at the corresponding locations are cross-correlated to obtain the time difference analysis results of different locations in that period.

[0026] A2. Change to a different monitoring period and repeat A1 until the required number of monitoring periods for analysis is reached.

[0027] This invention also discloses a CO2 time-shift analysis system based on zero-biased DAS-VSP data, used to implement the aforementioned CO2 time-shift analysis method based on zero-biased DAS-VSP data, comprising:

[0028] The acquisition module is used to acquire zero-bias DAS-VSP data at different times. The zero-bias DAS-VSP data includes basic data and monitoring data at different times. The basic data includes VSP data detected when no CO2 is injected, and the monitoring data includes VSP data after CO2 is injected.

[0029] The selection module is used to select data from the basic data and the monitoring data, respectively, the data of the depth segment with a signal-to-noise ratio higher than a first threshold, as the first intermediate data and the second intermediate data;

[0030] The separation module is used to separate the first intermediate data and the second intermediate data to obtain the corresponding first uplink reflected wave field data and the second uplink reflected wave field data respectively;

[0031] The uplink reflected wave field first arrival picking module is used to pick up the uplink reflected wave field first arrival time at different positions from the first uplink reflected wave field data and the second uplink reflected wave field data respectively, and let the uplink reflected wave field first arrival time corresponding to the first uplink reflected wave field data be the first uplink reflected wave field first arrival time, and let the uplink reflected wave field first arrival time corresponding to the second uplink reflected wave field data be the second uplink reflected wave field first arrival time;

[0032] The analysis module is used to perform cross-correlation time difference calculation on the first arrival time of the first up-reflected wave field at different locations and the first arrival time of the second up-reflected wave field at different times, and finally obtain the pre-stack time difference analysis results at different times. CO2 time shift analysis is performed based on the pre-stack time difference analysis results at different times.

[0033] The present invention also discloses an electronic device, including at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform a CO2 time-shift analysis method based on zero-bias DAS-VSP data as described above.

[0034] The present invention also discloses a storage medium storing a computer program, which, when executed by a processor, implements the aforementioned CO2 time-shift analysis method based on zero-bias DAS-VSP data.

[0035] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0036] This invention utilizes monitoring data from different periods of zero-biased DAS VSP to perform pre-stack time difference analysis. By monitoring the distribution and dynamic changes of underground carbon dioxide, it assesses whether CO2 is effectively stored as expected, demonstrating the practicality of this method. Attached Figure Description

[0037] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings:

[0038] Figure 1 This is a flowchart of the process described in this invention.

[0039] Figure 2 This is a schematic diagram of the observation system after loading data from different periods of the input vertical seismic profile zero-bias DAS VSP. The horizontal axis represents depth (in meters), and the vertical axis represents time (in milliseconds).

[0040] Figure 3 To select data from different periods, data were collected at depths of 600-850m before and after deconvolution. The horizontal axis represents depth (in meters), and the vertical axis represents time (in milliseconds).

[0041] Figure 4 The up-reflected wave field at a depth of 600-850m was selected for different periods; the horizontal axis represents depth (unit: meters), and the vertical axis represents time (unit: milliseconds).

[0042] Figure 5 Time difference analysis for different periods with zero bias; the horizontal axis of the upper graph is time (unit: milliseconds), and the vertical axis of the upper graph is time (unit: meters); the horizontal axis of the lower graph is time (unit: milliseconds), and the vertical axis of the lower graph is time (unit: meters). Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0044] Typically, DAS-VSP is used for fine-grained velocity and reservoir studies near the well, offering advantages such as high resolution and reservoir-oriented approach. In recent years, several time-lapse monitoring projects have been implemented both domestically and internationally. Time-lapse VSP is a seismic exploration technique that monitors changes in subsurface geological structures or fluid properties over time by repeatedly performing VSP measurements at different time points.

[0045] Therefore, this invention designs a CO2 time-shift analysis method, which analyzes the time shift of CO2 by using the difference between DAS-VSP data before and after CO2 injection. This method picks up the first arrival of the direct wave from the zero-bias DAS-VSP data, uses median filtering to separate the reflected wave field to obtain the up-reflected wave field, picks up the first arrival of the reflected wave at different depths, and then performs multi-period time difference time-shift analysis, thereby realizing CO2 monitoring time-shift analysis from the up-down wave field time difference results in multi-period zero-bias DAS-VSP data.

[0046] Next, the method of the present invention will be described in detail.

[0047] This embodiment 1 provides a CO2 time-shift analysis method based on zero-biased DAS-VSP data, such as Figure 1 As shown, it includes:

[0048] S1. Collect zero-bias DAS-VSP data at different times. The zero-bias DAS-VSP data includes basic data and monitoring data at different times. The basic data includes VSP data detected when no CO2 is injected, and the monitoring data includes VSP data after CO2 is injected.

[0049] Input DASVSP data (including base data and monitor data) collected at different periods of zero bias into the loading observation system. The base data and monitor data are denoted as DATA_B and DATA_M, respectively.

[0050] S2. Select data from the basic data and the monitoring data in depth segments with a signal-to-noise ratio higher than a first threshold as the first intermediate data and the second intermediate data, respectively; the first intermediate data is labeled as DATA_B. ′ The second intermediate data is marked as

[0051] DATA_M′.

[0052] In this embodiment, data from the depth range with a signal-to-noise ratio higher than a first threshold are selected from the basic data and the monitoring data as the first intermediate data and the second intermediate data. In this embodiment, the first threshold is 20 dB.

[0053] For example, if the data signal-to-noise ratio is higher than 20 dB at a depth range of 600–800 m, then that depth range should be selected.

[0054] S3. Separate the first intermediate data and the second intermediate data to obtain the corresponding first uplink reflected wave field data and the second uplink reflected wave field data;

[0055] In this embodiment, the specific process of separating the first intermediate data to obtain the first uplink reflected wavefield data is as follows:

[0056] The first intermediate data is deconvolved to eliminate the influence of multiple waves on the first ascending wave field analysis, thus obtaining the third intermediate data.

[0057] 1) Use the data DATA_B selected in step S2 ′ Deconvolution is performed to eliminate the influence of multiple waves on the up-going wave field analysis.

[0058] DATA1_B = Decon(DATA_B′);

[0059] Decon performs deconvolution on the data to obtain the deconvolutioned data, and DATA1_B represents the third intermediate data.

[0060] Wavefield separation is performed on the third intermediate data to remove the downlink wavefield data, thereby obtaining the first uplink reflected wavefield data.

[0061] Using the deconvolutioned data from step 1), wavefield separation needs to be performed on the deconvolutioned data to remove the downlink wavefield and obtain the uplink reflected wavefield data. The depth segment with high signal-to-noise ratio and relatively stable waveform is then extracted.

[0062] DATA2_B = Median(DATA1_B)

[0063] Median is used to separate the wavefield of the data to obtain the uplink reflected wavefield data, and DATA2_B is the first uplink reflected wavefield data.

[0064] In this embodiment, the specific process of separating the second uplink reflected wavefield data from the second intermediate data is as follows:

[0065] The second intermediate data is deconvolved to eliminate the influence of multiple waves on the up-wave field analysis, resulting in the fourth intermediate data.

[0066] 2) Use the data DATA_M selected in step S2 ′ Deconvolution is performed to eliminate the influence of multiple waves on the up-going wave field analysis.

[0067] DATA1_M = Decon(DATA_M′)

[0068] Decon performs deconvolution on the data to obtain the deconvolutioned data, and DATA1_M represents the fourth intermediate data.

[0069] Wavefield separation is performed on the fourth intermediate data to remove the downlink wavefield data, thereby obtaining the second uplink reflected wavefield data.

[0070] Using the deconvolutioned data from step 2), wavefield separation needs to be performed on the deconvolutioned data to remove the downlink wavefield and obtain the uplink reflected wavefield data.

[0071] DATA2_M = Median(DATA1_M)

[0072] Median is used to separate the wavefield of the data to obtain the uplink reflected wavefield data, and DATA2_M is the second uplink reflected wavefield data.

[0073] S4. Pick up the initial arrival time of the uplink reflected wave field at different positions from the first uplink reflected wave field data and the second uplink reflected wave field data respectively, and let the initial arrival time of the uplink reflected wave field corresponding to the first uplink reflected wave field data be the first uplink reflected wave field initial arrival time, and let the initial arrival time of the uplink reflected wave field corresponding to the second uplink reflected wave field data be the second uplink reflected wave field initial arrival time.

[0074] In this embodiment, the first arrival times of the up-reflected wave field at different locations are picked up, including the upper part of the gas injection layer, the gas injection layer, and the lower part of the gas injection layer.

[0075] The gas injection layer is where carbon dioxide is injected, and it has a precise depth.

[0076] Specifically, the initial arrival time of the upward reflected wave field above the gas injection layer in the basic data is defined as FB1_B, the initial arrival time of the upward reflected wave field above the gas injection layer is defined as FB2_B, and the initial arrival time of the upward reflected wave field below the gas injection layer is defined as FB3_B. Similarly, the initial arrival time of the upward reflected wave field above the gas injection layer in the monitoring data is defined as FB1_M, the initial arrival time of the upward reflected wave field above the gas injection layer is defined as FB2_M, and the initial arrival time of the upward reflected wave field below the gas injection layer is defined as FB3_M.

[0077] The first arrival of reflected wave fields at different locations is picked up using DATA2 data (DATA2_B, DATA2_M) and saved to the data headers at different locations. The locations where reflected waves are picked up can be divided into the upper part of the gas injection layer, the gas injection layer and the lower part of the gas injection layer, denoted as FB1 (FB1_B, FB1_M), FB2 (FB2_B, FB2_M), and FB3 (FB3_B, FB3_M), respectively.

[0078] S5. Cross-correlation time difference calculation is performed on the first arrival time of the first up-reflected wave field at different locations and the first arrival time of the second up-reflected wave field at different times to obtain the pre-stack time difference analysis results at different times. CO2 time shift analysis is performed based on the pre-stack time difference analysis results at different times.

[0079] The specific process involves cross-correlation of the first arrival time of the first up-reflected wavefield at different locations and the first arrival time of the second up-reflected wavefield at different times to obtain the pre-stack time difference analysis results for different periods.

[0080] A1. For the first arrival time of the second uplink reflected wave field at different locations corresponding to the monitoring data of a certain period, the first arrival time of the first uplink reflected wave field and the first arrival time of the second uplink reflected wave field at the corresponding locations are cross-correlated to obtain the time difference analysis results of different locations in that period.

[0081] A2. Change to a different monitoring period and repeat A1 until the required number of monitoring periods for analysis is reached.

[0082] Because the velocity of CO2 injection into the formation varies, the arrival time of the reflected wave field from data collected at different times will differ. This difference is used to determine the time difference caused by CO2 injection, and the magnitude of the time difference is used to determine whether CO2 is trapped in the formation.

[0083] The magnitude of the time difference can determine whether there is a risk of leakage in CO2 injection analysis. Since CO2 injection affects the velocity of the formation, the velocity affects the arrival time of the reflected waves of each data acquisition. By analyzing the time difference, we can determine the impact of CO2 injection on the data. If CO2 is not within this range (if the two time differences are equal or do not change, it means that no CO2 has been injected into the formation), then there will be no difference in wavefield time difference.

[0084] For example, based on the first arrival time of the second uplink reflected wave field of the first monitoring data, time difference analysis results can be obtained for different locations (above the gas injection layer, within the gas injection layer, and below the gas injection layer), as follows:

[0085] Time1=Corrlate(FB1_B,FB1_M);

[0086] Time2=Corrlate(FB2_B,FB2_M);

[0087] Time3=Corrlate(FB3_B,FB3_M);

[0088] Time1, Time2, and Time3 represent the time difference analysis results of the first monitoring data and the basic data above, below, and at the gas injection layer, respectively, i.e., the time difference analysis results of three different depth segments.

[0089] Because observation data from different periods were collected, time difference analysis results for the upper, lower, and upper layers of the gas injection layer can be obtained, namely Time1, Time2, and Time3 for different periods, thus obtaining pre-stack time difference analysis results for multi-period data.

[0090] The invention will now be illustrated through specific implementation examples.

[0091] 1) Input DAS-VSP zero-bias data (DATA) from multiple monitoring periods at different times, and load the observation system as follows: Figure 2 .

[0092] 2) Use the data (DATA_B) from step 1) to pick up the first arrival of the direct wave of the data, save the picking result to the data header, and select the depth segment with high data signal-to-noise ratio to pick up the first arrival of the direct wave as FB_B.

[0093] 3) DATA1_B = Decon(DATA_B) ′ ),

[0094] Decon is a function that performs deconvolution on the data to obtain deconvolutioned data, thus eliminating the impact of multiple waves on time difference analysis.

[0095] 4) DATA2_B = Median(DATA1_B)

[0096] Median involves performing wavefield separation on the data to obtain the uplink reflected wavefield. This uplink reflected wavefield data is then processed by first arrival picking and extracting depth segments with high signal-to-noise ratios and relatively stable waveforms. Figure 3 .

[0097] 5) Use the DATA2_B data from step 4) to pick up the first arrival of the reflected wave field at different locations and save it to the data header at different locations. The locations for picking up the reflected wave can be divided into those above the gas injection layer, those below the gas injection layer, and those below the gas injection layer, denoted as FB1_B, FB2_B, and FB3_B, respectively. Figure 4 , Figure 4 FB_B represents the first arrival time of the direct wave.

[0098] 6) Calculate the time difference by cross-correlation of data from different periods using the initial arrival of the reflected wave. Repeat steps 1-5 above to calculate the time difference of the monitoring data. Then perform time shift and time difference analysis on the monitoring data and the baseline data. (The results are as follows...) Figure 5 The data from different periods shows that the impact of continuously increasing CO2 injection on the time difference has further expanded. Two different time difference analyses lead to the conclusion that the increased impact of CO2 injection on the time difference indicates that there is no risk of CO2 leakage.

[0099] In summary, this invention provides a method for analyzing time-shifted earthquakes, which can monitor changes caused by CO2 injection through seismic means, providing a scientific basis for underground safety monitoring of CO2 injection.

[0100] Example 2 also discloses a CO2 time-shift analysis system based on zero-biased DAS-VSP data for performing the method of Example 1, including:

[0101] The acquisition module is used to acquire zero-bias DAS-VSP data at different times. The zero-bias DAS-VSP data includes basic data and monitoring data at different times. The basic data includes VSP data detected when no CO2 is injected, and the monitoring data includes VSP data after CO2 is injected.

[0102] The selection module is used to select data from the basic data and the monitoring data, respectively, the data of the depth segment with a signal-to-noise ratio higher than a first threshold, as the first intermediate data and the second intermediate data;

[0103] The separation module is used to separate the first intermediate data and the second intermediate data to obtain the corresponding first uplink reflected wave field data and the second uplink reflected wave field data respectively;

[0104] The uplink reflected wave field first arrival picking module is used to pick up the uplink reflected wave field first arrival time at different positions from the first uplink reflected wave field data and the second uplink reflected wave field data respectively, and let the uplink reflected wave field first arrival time corresponding to the first uplink reflected wave field data be the first uplink reflected wave field first arrival time, and let the uplink reflected wave field first arrival time corresponding to the second uplink reflected wave field data be the second uplink reflected wave field first arrival time;

[0105] The analysis module is used to perform cross-correlation time difference calculation on the first arrival time of the first up-reflected wave field at different locations and the first arrival time of the second up-reflected wave field at different times, and finally obtain the pre-stack time difference analysis results at different times. CO2 time shift analysis is performed based on the pre-stack time difference analysis results at different times.

[0106] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for CO2 time-shift analysis based on zero-biased DAS-VSP data, characterized in that, include: Zero-bias DAS-VSP data were collected at different times. The zero-bias DAS-VSP data included basic data and monitoring data at different times. The basic data included VSP data detected when no CO2 was injected, and the monitoring data included VSP data after CO2 was injected. Data with a signal-to-noise ratio higher than a first threshold are selected from the basic data and the monitoring data, respectively, as the first intermediate data and the second intermediate data. The first intermediate data and the second intermediate data are deconvolutionally processed to eliminate multiple waves, and then wavefield separation is performed to remove the downlink wavefield, thereby obtaining the corresponding first uplink reflected wavefield data and second uplink reflected wavefield data. From the first and second uplink reflected wave field data, the initial arrival time of the uplink reflected wave field is picked from three different locations: above the gas injection layer, the gas injection layer, and below the gas injection layer. The initial arrival time of the uplink reflected wave field corresponding to the first uplink reflected wave field data is designated as the first uplink reflected wave field initial arrival time, and the initial arrival time of the uplink reflected wave field corresponding to the second uplink reflected wave field data is designated as the second uplink reflected wave field initial arrival time. The first arrival time of the first up-reflected wave field at different locations and the first arrival time of the second up-reflected wave field at different times are cross-correlated and the time difference is calculated. Finally, the pre-stack time difference analysis results at different times are obtained, and CO2 time shift analysis is performed based on the pre-stack time difference analysis results at different times. The determination of whether CO2 is sequestered in the formation is based on the magnitude of the time difference. The specific process is as follows: A1. For the first arrival time of the second uplink reflected wave field at different locations corresponding to the monitoring data of a certain period, the first arrival time of the first uplink reflected wave field and the first arrival time of the second uplink reflected wave field at the corresponding locations are cross-correlated to obtain the time difference analysis results of different locations in that period. A2. Change to a different monitoring period and repeat A1 until the required number of monitoring periods for analysis is reached.

2. The CO2 time-shift analysis method based on zero-biased DAS-VSP data according to claim 1, characterized in that, The first threshold is 20 dB.

3. The CO2 time-shift analysis method based on zero-biased DAS-VSP data according to claim 1, characterized in that, The gas injection layer, the upper gas injection layer, and the lower gas injection layer are all located within a depth range where the data signal-to-noise ratio is higher than a set first threshold.

4. A CO2 time-shift analysis system based on zero-biased DAS-VSP data, used to implement the CO2 time-shift analysis method based on zero-biased DAS-VSP data as described in any one of claims 1-3, characterized in that, include: The acquisition module is used to acquire zero-bias DAS-VSP data at different times. The zero-bias DAS-VSP data includes basic data and monitoring data at different times. The basic data includes VSP data detected when no CO2 is injected, and the monitoring data includes VSP data after CO2 is injected. The selection module is used to select data from the basic data and the monitoring data, respectively, the data of the depth segment with a signal-to-noise ratio higher than a first threshold, as the first intermediate data and the second intermediate data; The separation module is used to separate the first intermediate data and the second intermediate data to obtain the corresponding first uplink reflected wave field data and the second uplink reflected wave field data respectively; The uplink reflected wave field first arrival picking module is used to pick up the uplink reflected wave field first arrival time at different positions from the first uplink reflected wave field data and the second uplink reflected wave field data respectively, and let the uplink reflected wave field first arrival time corresponding to the first uplink reflected wave field data be the first uplink reflected wave field first arrival time, and let the uplink reflected wave field first arrival time corresponding to the second uplink reflected wave field data be the second uplink reflected wave field first arrival time; The analysis module is used to perform cross-correlation time difference calculation on the first arrival time of the first up-reflected wave field at different locations and the first arrival time of the second up-reflected wave field at different times, and finally obtain the pre-stack time difference analysis results at different times. CO2 time shift analysis is performed based on the pre-stack time difference analysis results at different times.

5. An electronic device, characterized in that, It includes at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform a CO2 time-shift analysis method based on zero-bias DAS-VSP data as described in any one of claims 1 to 3.

6. A storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a CO2 time-shift analysis method based on zero-biased DAS-VSP data as described in any one of claims 1 to 3.

Images